14 research outputs found

    Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

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    <p>Abstract</p> <p>Background</p> <p>Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.</p> <p>Methods</p> <p>In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.</p> <p>Results</p> <p>Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.</p> <p>Conclusions</p> <p>Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.</p

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Abstract: Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Genome-Wide Association Study of Short-Acting β2-Agonists. A Novel Genome-Wide Significant Locus on Chromosome 2 near ASB3

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    Rationaleβ2-Agonists are the most common form of treatment of asthma, but there is significant variability in response to these medications. A significant proportion of this responsiveness may be heritable.ObjectivesTo investigate whether a genome-wide association study (GWAS) could identify novel pharmacogenetic loci in asthma.MethodsWe performed a GWAS of acute bronchodilator response (BDR) to inhaled β2-agonists. A total of 444,088 single-nucleotide polymorphisms (SNPs) were examined in 724 individuals from the SNP Health Association Resource (SHARe) Asthma Resource Project (SHARP). The top 50 SNPs were carried forward to replication in a population of 444 individuals.Measurements and main resultsThe combined P value for four SNPs reached statistical genome-wide significance aftercorrecting for multiple comparisons. Combined P values for rs350729, rs1840321, rs1384918, and rs1319797 were 2.21 × 10(-10), 5.75 × 10(-8), 9.3 × 10(-8), and 3.95 × 10(-8), respectively. The significant variants all map to a novel genetic region on chromosome 2 near the ASB3 gene, a region associated with smooth muscle proliferation. As compared with the wild type, the presence of the minor alleles reduced the degree of BDR by 20% in the original population and by a similar percentage in the confirmatory population.ConclusionsThese GWAS findings for BDR in subjects with asthma suggest that a gene associated with smooth muscle proliferation may influence a proportion of the smooth muscle relaxation that occurs in asthma

    Genome-Wide Association Study of Short-Acting beta(2)-Agonists A Novel Genome-Wide Significant Locus on Chromosome 2 near ASB3

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    Rationale: [beta(2)-Agonists are the most common form of treatment of asthma, but there is significant variability in response to these medications. A significant proportion of this responsiveness may be heritable. Objectives: To investigate whether a genome-wide association study (GWAS) could identify novel pharmacogenetic loci in asthma. Methods: We performed a GWAS of acute bronchodilator response (BDR) to inhaled beta(2)-agonists. A total of 444,088 single-nucleotide polymorphisms (SNPs) were examined in 724 individuals from the SNP Health Association Resource (SHARe) Asthma Resource Project (SHARP). The top 50 SNPs were carried forward to replication in a population of 444 individuals. Measurements and Main Results: The combined P value for four SNPs reached statistical genome-wide significance after correcting for multiple comparisons. Combined P values for rs350729, rs1840321, rs1384918, and rs1319797 were 2:21 X 10(-10), 5.75 X 10(-8), 9.3 X 10(-8), 3.95 X 10(-8), respectively. The significant variants all map to a novel genetic region on chromosome 2 neat the ASB3 gene, a region associated with smooth muscle proliferation. As compared with the wild type, the presence of the minor alleles reduced the degree of BDR by 20% in the original population and by a similar percentage in the confirmatory population. Conclusions: These GWAS findings for BDR in subjects with asthma suggest that a gene associated with smooth muscle proliferation may influence a proportion of the smooth muscle relaxation that occurs in asthma
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